jpeg-matlab

说明：  本部分源码是处理静态图像时候，需要的一部分代码，希望对于那些正在研究图像处理技术的朋友有用。(This section is the source when dealing with a static image, the need for part of the code, I hope for those who are studying image processing technology useful friends.)

matlab编写计算直边图像的点扩散函数PSF(Compiling Point Spread Function ( PSF) for Computing Straight Edge Images with MATLAB)

基于CDD模型的快速数字图像修复算法 matlab版 (CDD model based on fast digital image restoration algorithm matlab version)

说明：  小波变换图像增强，经过matlab6.0测试，放心可用(Wavelet image enhancement, after matlab6.0 testing, confidence can be)

根据GetVersionEx获取版本ID获取系统名称(According GetVersionEx version ID for the system to obtain the name of)

去散射和边缘增强是水下图像从严重细节损失、颜色偏移和模糊中提取的关键步骤。本文提出了一种增强水下图像对比度和边缘的新方法。(De-scattering and edge enhancing are critical procedures for underwater images which surfer from serious detail loss, color deviation and blurring. In this work, a novel method has been proposed to enhance contrast and edge of underwater images.)

matlab加载一个视屏，转化成每帧图片加以保存。(Matlab loads a video screen and translates it into pictures for each frame to be saved.)

利用c++实现图像转置源代码，像素变换的一种方式(use Image home to the source code, pixel transform the way)

IMAGING 工业相机图像灰度特征处理源代码，文件源码中集成了三方组件，非常有价值(IMAGING industrial camera image grayscale image processing source code, the source code to integrate the three party components, very valuable)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)